Overcoming generative AI and cloud computing challenges
Cloud computing is both a challenge and an opportunity for established companies. Despite the draw of the cloud’s benefits, such as scalability, flexibility, and cost-efficiency, many organizations find themselves fighting with complexities of migration and the realization of tangible value from their investments. Surprisingly, even after years of concerted efforts, the average large company has migrated only a fraction—around 15 to 20 percent—of its applications to the cloud. There’s a palpable aspiration among enterprises to expand their cloud footprint, with ambitions to host a majority of their applications on public cloud platforms within the next five to seven years.
Opportunities from generative AI
The economic implications of the joining of generative AI and cloud computing are undeniable. Projections suggest that cloud computing could yield approximately $3 trillion in EBITDA by the year 2030, with the potential for a substantial 20 to 30 percent uplift in EBITDA across various industry sectors. Generative AI is positioned to amplify these gains further, potentially adding an additional 75 to 110 percentage points of incremental ROI to cloud programs. This comes from the unlocking of new business use cases, the reduction of migration costs and timelines, and the augmentation of overall productivity through AI-driven automation and optimization.
Economic impact and ROI:
To maximize the ROI of cloud investments in this new paradigm, organizations must work on strategic plans. Successful companies prioritize extensive foundations for their cloud environments, covering scalable architectures, resilient infrastructure, and rigorous security protocols. Adopting product-oriented operating models lets organizations iterate rapidly, respond to evolving market demands, and extract maximum value from their cloud initiatives.
Challenges in cloud value realization
Generative AI is disrupting the dynamics of cloud ROI. Generative AI technologies, with their ability to autonomously create content, simulate scenarios, and optimize processes, promise to expedite cloud adoption while simultaneously unlocking novel business and technological use cases. With generative AI, organizations can accelerate their cloud programs, bridging the gap between investment and value realization.
Current cloud adoption rates:
Maximizing the benefits of cloud computing is riddled with challenges, chief among them being the significant transformation required to adapt legacy IT infrastructures optimized for on-premises operations to the cloud environment. These infrastructures, painstakingly built over decades, now demand extensive reconfiguration and modernization efforts to align with the requirements of cloud-native architectures and services. This transformation journey, laden with complexities and uncertainties, often impedes organizations from realizing the full potential of their cloud investments.
Strategies for maximizing cloud ROI
Three primary sources of lost value in cloud programs include unrealized use cases, cloud sprawl, and stalled adoption. Unrealized use cases refer to scenarios where organizations fail to identify and capitalize on opportunities for innovation and efficiency enabled by the cloud. Cloud sprawl happens when organizations lose control over their cloud resources, leading to inefficiencies, security vulnerabilities, and increased costs. Lastly, stalled adoption comes when organizations struggle to execute their cloud strategies effectively, leading to delays, cost overruns, and ultimately, diminished returns on investment.
Practical recommendations
Avoiding and repairing damage from these risks takes a custom approach that combines strategic foresight, technological prowess, and organizational agility.
Firstly, organizations must perform assessments of their existing IT situation to identify potential use cases for cloud adoption and generative AI integration. This covers evaluating the feasibility, business impacts, and the technical requirements of each initiative to prioritize investments effectively.
Secondly, organizations must have strong governance frameworks to manage their cloud resources efficiently and mitigate the risks of cloud sprawl. Establishing clear policies, processes, and controls to govern resource provisioning, usage monitoring, and cost optimization.
Lastly, organizations must invest in talent development and organizational change management for a culture of innovation, collaboration, and continuous improvement. This includes providing employees with the necessary skills, tools, and support to embrace new technologies, adapt to evolving business requirements, and drive meaningful change across the organization.
